AWS Data Engineer Resume Example & Writing Guide
Use this AWS Data Engineer resume example and guide to improve your career and write a powerful resume that will separate you from the competition.
If you’re interested in working with big data, but aren’t sure where to start, becoming a data engineer might be the perfect job for you. Data engineers work with large datasets to collect insights and build solutions that help companies run more efficiently. They use their coding skills to create tools that automate tedious tasks and free up their coworkers to focus on more important things.
Data engineers often work closely with data analysts and data scientists to identify trends and create reports. They might also collaborate with product managers to help develop new features or build tools that improve user experience. And because data engineers work in such a diverse field, they have the opportunity to work on a variety of different types of projects.
Here are some tips and an example to help you write a fantastic data engineer resume that will get you noticed by recruiters.
How to Write an AWS Data Engineer Resume
Here’s how to write an resume of your own.
Write Compelling Bullet Points
The best resumes are clear and concise. They focus on the most relevant experience and bullet points, and they use specific language to describe projects and responsibilities.
For example, rather than saying you “managed data for large-scale analytics platform,” you could say you “managed data for Amazon Web Services (AWS) data analytics platform, providing insights for over 1,000 users across six departments.”
The second bullet point is much stronger because it provides more detail about the project and the results of your work. It also mentions the name of the company and the number of people who used the platform, which makes the project seem even more impressive.
Identify and Include Relevant Keywords
When you apply for a job as a data engineer, your resume is usually scanned by an applicant tracking system (ATS) for certain keywords. If your resume doesn’t include enough of the right keywords, your application might not make it past the initial screening process.
That’s why it’s important to include keywords in your resume. You can find these keywords by reading through the job posting and including terms that are repeated in your resume.
- Amazon Web Services (AWS)
- Python (Programming Language)
- Git
- SQL
- Unix
- Bash
- Data Engineering
- Machine Learning
- R (Programming Language)
- Databases
- JavaScript
- Apache Spark
- Data Analysis
- Scala
- Data Science
- Hadoop
- Linux
- AWS Lambda
- Agile Methodologies
- Algorithms
- Big Data
- MySQL
- Microsoft SQL Server
- Scrum
- Shell Scripting
- Amazon EC2
- Microservices
- DevOps
- HTML5
- TypeScript
Showcase Your Technical Skills
As an AWS data engineer, you need to be proficient in a variety of software programs and systems in order to effectively manage and process data. Some of the most commonly used programs and systems include Amazon S3, Amazon EMR, Amazon Athena, and Amazon Redshift. Additionally, you should have a solid understanding of big data concepts and be able to effectively use tools like Hadoop, Hive, and Spark.